Displaying results 1 - 3 of 3
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Using clinician mental models to guide annotation of medically unexplained symptoms and syndromes found in VA clinical documents
Content Type: Abstract
Medically unexplained syndromes (MUS) are conditions that are diagnosed on the basis of symptom constellations and are characterized by a lack of well-defined pathogenic pathways. The three most common MUS are chronic fatigue … read more… Medically unexplained syndromes (MUS) are conditions that are diagnosed on the basis of … well-defined pathogenic pathways. The three most common MUS are chronic fatigue syndrome, irritable bowel syndrome, … Patients often meet the criteria for more than one MUS. Objectives We sought to develop a guideline and … -
Identification of features for detection and prediction of homelessness from VA clinical documents
Content Type: Abstract
Homelessness in general is a major issue in the US today. The risk factors of homelessness are myriad, including inadequate income, lack of affordable housing, mental health and substance abuse issues, lack of social support, and nonadherence to… read more… identification of these factors from clinical documents may help detect or even predict homelessness cases, allowing … iden- tification of these factors from clinical documents may help detect or even predict homelessness cases, allowing … identification of these factors from clinical documents may help detect or even predict homelessness cases, allowing … -
Standardization to aid interoperability between NLP system
Content Type: Abstract
There are a number of Natural Language Processing (NLP) annotation and Information Extraction (IE) systems and platforms that have been successfully used within the medical domain. Although these groups share components of their systems, there… read more… IN, USA; and 11NLM, Bethesda, MD, USA E-mail: guy.divita@hsc.utah.edu Objective The Consortium for …